Optimizing Pork Chilling Using Numerical Modeling
Jenni L. Briggs and Elisabeth Huff-Lonergan, Department of Agricultural and Biosystems Engineering
Department of Animal Science, Iowa State University, Ames, IA
Introduction
Optimal operating parameters of pork chilling systems remain somewhat of a mystery to the pork industry and academics. As evidence, the National Pork Producers Council recently (November 2, 1999) sponsored an informative workshop on chilling. Chilling is a balance between pork quality, pork safety, and economics. Previous research has focused toward quality indicators including post-mortem biochemical changes in pH (Maribo et al., 1998), sensory characteristics including color and texture, physical shrink (Jones et al., 1993;1988), and microbial load (Jones et al., 1991) as attributed to chilling rate. These measures provide insight into chilling efficacy and point out the need for optimizing carcass-chilling systems. What the optimal operating parameters of chillers (air temperature, air velocity, air humidity, configuration of pork carcasses in the chiller room) are, and how these operating parameters affect chilling rate and quality remain unknown. Before these types of questions may be answered, a clear understanding of airflow patterns around the carcass during chilling, and heat and mass transfer characteristics is needed. Upon filling this gap in the knowledge, more control over the chilling process is possible resulting in higher pork quality, and value.
Numerous factors contribute to the chilling rate of pork carcasses: thermal conductivities of the pork, initial carcass temperature, air temperature, and air velocities. To understand the chilling process, and the relationship between the previously mentioned variables, a model to predict the airflow patterns, heat transfer rate, and mass transfer rate in chilling operations is necessary. Benefits of modeling to predict complicated transport processes include optimizing system operations, decreasing design time, and saving resources put toward prototyping. In pork chilling, analytical models have been proposed to evaluate heat transfer rates of pork carcasses (Kuitche et al., 1996a; Kuitche et al., 1996b). The primary limitation of analytical models is that they require an assumption of simple geometric shapes (cylindrical, spherical, rectangular), whereas a pork carcass is a complex shape.
An alternative numerical modeling approach is finite element analysis (FEA). Advantages of FEA are non-limiting geometric shapes, and the ability to vary physical properties across the solid body. Using this modeling technique, the domain is divided into mesh elements (Figure 1), and the governing differential equations of heat, mass, and momentum transport are solved at each node (the apex of the element for a quadrilateral 4-noded element). The availability of commercial software has made this analysis method an invaluable tool for use in process design.
The overall objective of this research is to investigate chilling rates of virtual pork carcasses as affected by processing parameters using finite element analysis to predict the effects of transport phenomena. Model findings for airflow patterns (momentum transfer) are presented in here. These results show the implication of flow rates and carcass spacing on air flow patterns. Ongoing research is focusing on the incorporation of heat transfer into the existing model, which will allow for the prediction of temperature profiles. It is expected later modeling work will then include mass transfer into the model.
Model Development
Commercially available software by Fluent (Evansville, IL) was used in this modeling work. A program called Gambit was used for mesh development and FIDAP was used to solve the problem.
Mesh Development
A two dimensional mesh was developed for the modeling airflow patterns as affected by airflow rates and carcass spacing. A typical mesh is shown in Figure 1. Depending on the virtual carcass spacing, 0.2 or 0.4 m, the mesh consisted of between 3538 – 4052 elements. A paved meshing scheme was developed and 4-noded quadrilateral elements were used.
Model Development
To solve the differential equations governing momentum transfer, boundary conditions must be specified. Airflow rates between 1 – 5 m/s positioned at the upper portion of the mesh were specified, which are typical in chilling operations. At these airflow rates the flow is most likely in the turbulent regime because Reynolds numbers of greater than 20,000 is used as a general guide for flow around an object for signifying turbulence. A no slip boundary condition was also specified at the surface of the virtual pork carcass.
Results and Discussion
Mesh Development
Numerous meshing schemes were developed prior to settling on a 2-D scheme. A 3-D scheme was originally implemented for full carcass investigation. However, the numbered of elements to obtain an acceptable mesh resolution resulted in a base model that required more computing power than available with the typical computer. Despite the simplification used in the portion of our study, this 2-D mesh still provides valuable information of airflow patterns between carcasses. Future work using a 3-D mesh is ongoing, and is discussed later.
Model Findings
Figure 2 shows velocity patterns of air around virtual pork carcasses separated by 0.4 meters caused by an inlet airflow rate of 1 m/s. The outer edges of the carcasses show an increased flow rate near the edges; however, it would be expected that this area on the modeled carcasses would be adjacent to another pork carcasses, which was not modeled in this case. At the upper portion of the ham, near the legs, air velocities are significantly decreased compared to the prescribed airflow inlet rate. As the portion of the hams from the two carcasses is closest, the flow velocity increases, which is expected because the air must move somewhere as the cross-section area is decreased.

Figure 2. Speed contour plot of air about two virtual pork carcasses with an inlet flow rate of 1 m/s and carcass separation distance of 0.2 m.
The most significant findings are predicted airflow between the two carcasses. Air velocities at a distance of 0.75 m from the top of the carcass, near the middle of the internal cavity, were plotted as a function of distance across the carcasses (Figure 3 and 4). When the carcass spacing is 0.2 m, the airflow between the chest cavity of on carcass and the back of another is considerably less than the prescribed inlet velocity for the model; the maximum air speed is roughly one-tenth. By increasing the separation distance of the carcasses to 0.4 m, the predicted airflow rate is similar to the prescribed rate. Therefore, this suggests that increasing the distance allows air to circulate more freely.

Figure 3. Velocity profile of airflow between carcasses spaced at 0.2 m apart and 0.75 m from top of the carcass.
The critical implication of airflow rates between carcasses requires the heat transfer portion of this work to be incorporated. Then, a better understanding of how the airflow affects the convective heat transfer coefficient, which governs how quickly the heat transfers from the carcass and away to the surrounding area.
Ongoing Research
Research is underway to develop heat transfer, which will allow for temperature profiles to be developed because considering the importance of chilling rate of the ham, a 3-D mesh of the ham portion has been developed. It is expected that concentrating solely on the ham portion will results in a FEA model, which can be solved using a typical computer. Concentrating on the ham only will cut the number of elements, or model size, by two-thirds compared to a whole carcass 3-D model.

Figure 4. Velocity profile of airflow between carcasses spaced at 0.4 m apart and 0.75 m from top of the carcass.
References
Jones, S.D.M., L.E. Jeremiah and W.M. Robertson. 1993. Meat Sci. 34:351-362.
Jones, S.D.M., G.G Greer, L.E. Jeremiah, A.C. Murray and W.M. Robertson. 1991. Meat Sci. 29:1-16.
Jones, S.D.M., A.C. Murray, and W.M. Robertson. 1988. Can. Inst. Food Sci. Technol. J. 21:102-105.
Kuitche, A., J.D. Daudin, and G. Letang. 1996a. J. Food Eng. 28:55-84.
Kuitche, A., G. Letang, and J.D. Daudin. 1996b. J. Food Eng. 28:85-107.
Maribo,-H.; Olsen,-E.V.; Barton-Gade,-P.; Moller,-A.J. 1998. Meat-Sci. 50:175-189.
Dr. Jenni Briggs
Dr. Jenni Briggs received her Ph.D. in agricultural engineering from Purdue University in 1999. Upon her degree completion she accepted her current position as an assistant professor in the Departments of Agricultural and Biosystems Engineering and Food Science and Human Nutrition at Iowa State University. Her research focus is food process engineering and rheology.